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Causal Analytics for Applied Risk Analysis / by Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun.

Cox Jr., Louis Anthony, author.; Popken, Douglas A., author.; Sun, Richard X., author.
2018
HD30.23
Available Online
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Title
Causal Analytics for Applied Risk Analysis / by Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun.
Author
Cox Jr., Louis Anthony, author.
ISBN
9783319782423 (electronic book)
3319782428 (electronic book)
3319782401
9783319782409
DOI
https://doi.org/10.1007/978-3-319-78242-3
Published
Cham : Springer International Publishing : Imprint : Springer, 2018.
Language
English
Description
1 online resource (XXII, 588 pages 121 illustrations, 95 illustrations in color.) : illustrations
Item Number
10.1007/978-3-319-78242-3 doi
Call Number
HD30.23
Dewey Decimal Classification
658.40301
Summary
Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives. The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.
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Digital File Characteristics
text file PDF
Added Author
Popken, Douglas A., author.
Sun, Richard X., author.
Series
International series in operations research & management science ; 270. 0884-8289
Available in Other Form
Print version: 9783319782409
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Part 1. Concepts and Methods of Causal Analytics
Chapter 1. Causal Analytics and Risk Analytics
Chapter 2. Causal Concepts, Principles, and Algorithms
Part 2. Descriptive Analytics in Public and Occupational Health
Chapter 3. Descriptive Analytics for Public Health: Socioeconomic and Air Pollution Correlates of Adult Asthma, Heart Attack, and Stroke Risks
Chapter 4. Descriptive Analytics for Occupational Health: Is Benzene Metabolism in Exposed Workers More Efficient at Very Low Concentrations?- Chapter 5. How Large are Human Health Risks Caused by Antibiotics Used in Food Animals?- Chapter 6. Quantitative Risk Assessment of Human Risks of Methicillin-Resistant Staphylococcus aureus (MRSA) Caused by Swine Operations Part 3. Predictive and Causal Analytics
Chapter 7. Attributive Causal Modeling: Quantifying Human Health Risks Caused by Toxoplasmosis From Open System Production Of Swine
Chapter 8. How Well Can High-Throughput Screening Test Results Predict Whether Chemicals Cause Cancer in Mice and Rats?- Chapter 9. Mechanistic Causality: Biological Mechanisms of Dose-Response Thresholds for Inflammation-Mediated Diseases Caused by Asbestos Fibers and Mineral Particles
Part 4. Evaluation Analytics
Chapter 10. Evaluation Analytics for Public Health: Has Reducing Air Pollution Reduced Mortality in the United States?- Chapter 11. Evaluation Analytics for Occupational health: How accurately and consistently do laboratories measure workplace concentrations of respirable crystalline silica?- Part 5. Risk Management: Insights from Prescriptive, Learning, and Collaborative Analytics
Chapter 12. Improving individual, group and organizational decisions: Overcoming learning aversion in evaluating and managing uncertain risks
Chapter 13. Improving organizational risk management: From Lame Excuses to Principled Practice
Chapter 14. Improving institutions of risk management: Uncertain causality and judicial review of regulations
Chapter 15. Intergenerational justice in protective and resilience investments with uncertain future preferences and resources.

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